@@ -79,17 +79,18 @@ The pose estimation work is based on the C++ code from [the ECCV 2016 demo](http
## Contents
1.[Installation, Reinstallation and Uninstallation](#installation-reinstallation-and-uninstallation)
2.[Custom Caffe](#custom-caffe)
3.[Quick Start](#quick-start)
2.[Quick Start](#quick-start)
1.[Demo](#demo)
2.[OpenPose Wrapper](#openpose-wrapper)
3.[OpenPose Library](#openpose-library)
4.[Output](#output)
5.[Speed Up Openpose And Benchmark](#speed-up-openpose-and-benchmark)
6.[Send Us Failure Cases!](#send-us-failure-cases)
7.[Send Us Your Feedback!](#send-us-your-feedback)
8.[Citation](#citation)
9.[Other Contributors](#other-contributors)
3.[Output](#output)
4.[Custom Caffe](#custom-caffe)
5.[Standalone Face Or Hand Keypoint Detector](#standalone-face-or-hand-keypoint-detector)
6.[Speed Up Openpose And Benchmark](#speed-up-openpose-and-benchmark)
7.[Send Us Failure Cases!](#send-us-failure-cases)
8.[Send Us Your Feedback!](#send-us-your-feedback)
9.[Citation](#citation)
10.[Other Contributors](#other-contributors)
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@@ -98,19 +99,6 @@ You can find the installation, reinstallation and uninstallation steps on: [doc/
## Custom Caffe
We only modified some Caffe compilation flags and minor details. You can use your own Caffe distribution, these are the files we added and modified:
1. Added files: `install_caffe.sh`; as well as `Makefile.config.Ubuntu14.example`, `Makefile.config.Ubuntu16.example`, `Makefile.config.Ubuntu14_cuda_7.example` and `Makefile.config.Ubuntu16_cuda_7.example` (extracted from `Makefile.config.example`). Basically, you must enable cuDNN.
2. Edited file: Makefile. Search for "# OpenPose: " to find the edited code. We basically added the C++11 flag to avoid issues in some old computers.
1. Run `make all && make distribute` in your Caffe version.
2. Open the OpenPose Makefile config file: `./Makefile.config.UbuntuX.example` (where X depends on your OS and CUDA version).
3. Modify the Caffe folder directory variable (`CAFFE_DIR`) to your custom Caffe `distribute` folder location in the previous OpenPose Makefile config file.
## Quick Start
Most users cases should not need to dive deep into the library, they might just be able to use the [Demo](#demo) or the simple [OpenPose Wrapper](#openpose-wrapper). So you can most probably skip the library details in [OpenPose Library](#openpose-library).
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@@ -151,6 +139,24 @@ Check the output (format, keypoint index ordering, etc.) in [doc/output.md](doc/
## Custom Caffe
We only modified some Caffe compilation flags and minor details. You can use your own Caffe distribution, these are the files we added and modified:
1. Added files: `install_caffe.sh`; as well as `Makefile.config.Ubuntu14.example`, `Makefile.config.Ubuntu16.example`, `Makefile.config.Ubuntu14_cuda_7.example` and `Makefile.config.Ubuntu16_cuda_7.example` (extracted from `Makefile.config.example`). Basically, you must enable cuDNN.
2. Edited file: Makefile. Search for "# OpenPose: " to find the edited code. We basically added the C++11 flag to avoid issues in some old computers.
1. Run `make all && make distribute` in your Caffe version.
2. Open the OpenPose Makefile config file: `./Makefile.config.UbuntuX.example` (where X depends on your OS and CUDA version).
3. Modify the Caffe folder directory variable (`CAFFE_DIR`) to your custom Caffe `distribute` folder location in the previous OpenPose Makefile config file.
## Standalone Face Or Hand Keypoint Detector
In case of hand camera views at which the hands are visible but not the rest of the body, or if you do not need the body keypoint detector and want to considerably speed up the process, you can use the OpenPose face or hand keypoint detectors with your own face or hand detectors, rather than using the body keypoint detector as initial detector for those. More information in [doc/standalone_face_or_hand_keypoint_detector.md#faq](doc/standalone_face_or_hand_keypoint_detector.md#faq).
## Speed Up OpenPose and Benchmark
Check the OpenPose Benchmark and some hints to speed up OpenPose on [doc/installation.md#faq](doc/installation.md#faq).
OpenPose Library - Standalone Face Or Hand Keypoint Detector
====================================
In case of hand camera views at which the hands are visible but not the rest of the body, or if you do not need the body keypoint detector and want to considerably speed up the process, you can use the OpenPose face or hand keypoint detectors with your own face or hand detectors, rather than using the body keypoint detector as initial detector for those.
## Standalone Face Keypoint Detector
There are 2 ways to add the OpenPose face keypoint detector to your own code without using the body pose keypoint extractor as initial face detector:
1. Easiest solution: Forget about the `OpenPose demo` and `wrapper/wrapper.hpp`, and instead use the `include/openpose/face/faceExtractor.hpp` class with the output of your face detector. Recommended if you do not wanna use any other OpenPose functionality.
2. Elegant solution: If you wanna use the whole OpenPose framework, simply copy `include/wrapper/wrapper.hpp` as e.g. `examples/userCode/wrapperFace.hpp`, and change our `FaceDetector` class by your custom face detector class. If you wanna omit the Pose keypoint detection, you can simply delete it from that custom wrapper too.
## Standalone Hand Keypoint Detector
The analogous steps apply to the hand keypoint detector, but modifying `include/openpose/hand/handExtractor.hpp`.
